Unintentional Racial Biases May Affect Economic, Trust Decisions

NEW YORK - Psychologists have found that people may make economic and trust decisions based on unconscious or unintentional racial biases. The study, conducted in the laboratory of New York University Professor Elizabeth Phelps, is published in the latest issue of the Proceedings of the National Academy of Sciences.

“Decisions in the worlds of business, law, education, medicine, and even more ordinary daily interactions between individuals, all rely on trust,” the researchers wrote. “In an increasingly globalized economy, that trust must be forged between individuals who differ in background, shared experiences, and aspirations.”

“These results provide evidence that decisions we may believe to be consciously determined are, in fact, not entirely so, and suggest that this may have a very real cost for individuals and society,” they continued. “Whom we trust is not only a reflection of who is trustworthy, but also a reflection of who we are.”

The field of psychology has generally concluded that there is a distinction between explicit and implicit mental processes, including attitudes, beliefs, and self-perceptions. Explicit mental processes involve intentional decisions or judgments while implicit mental processes occur relatively automatically and without awareness. In the PNAS study, the researchers focused on implicit social bias, a measure of how strongly one associates a concept—for instance, “pleasant” or “unpleasant”—with different social groups. Recent scholarship has shown implicit biases are pervasive and can predict social behaviors, including the decisions of highly trained professionals such as doctors.

Employing a commonly used Implicit Association Test (IAT), researchers asked 50 racially diverse participants to rate the trustworthiness of individuals depicted in just under 300 photographs of Black, White, Asian, Hispanic, and mixed race men on a scale from one (“not-at-all trustworthy”) to nine (“extremely trustworthy”). The participants were instructed to report their initial “gut impressions.”

The researchers found that the participants’ implicit race attitudes, measured in a subsequent test, predicted disparities in the perceived trustworthiness of Black and White faces. Individuals whose tests demonstrated a stronger pro-White implicit bias were more likely to judge White faces as more trustworthy than Black faces, and vice versa, regardless of that individual’s own race or explicit beliefs.

In a similar experiment using another group of participants, the researchers assessed how implicit racial biases may affect economic or business decisions. Participants were shown the images of the same individuals used in the first experiment and told these individuals were the subjects’ partners and had been previously interviewed by the experimenter. Participants then had to make decisions about how much money they would risk with these partners.

The researchers found that participants’ implicit racial biases predicted racial disparities in the amounts of money participants were willing to risk in this trust-based interpersonal economic interaction. Specifically, individuals whose IAT scores reflected a stronger pro-White implicit bias were likely to offer more money to White than Black partners and vice versa.

According to the authors, the results suggest that implicit biases toward social groups may drive rapid evaluations of unfamiliar individuals in the absence of additional information, despite our conscious desires and intentions.

While the study’s subjects in both experiments included multiple racial groups, the race of the participants did not account for the findings.

“There is not a simple correspondence between individuals' implicit racial attitudes and their own race,” the researchers explained. “Implicit attitudes are thought to result from many sources beyond one’s own race, including environmental exposure and personal interactions.”

The authors were: Damian Stanley and Peter Sokol-Hessner, graduates of NYU’s doctoral program in neural science and now post-doctoral research fellows at the California Institute of Technology (Caltech); Mahzarin Banaji, a professor in Harvard University’s Department of Psychology; and Phelps, a professor of psychology and neural science.